It’s easier than ever to test and optimise LinkedIn content campaigns
Our new Direct Sponsored Content duplication figure means you can AB test different elements with just a few clicks
July 10, 2017
A/B testing should be a key component of any B2B content marketing strategy – and we know from our own experience that it can deliver huge benefits when sponsoring content on LinkedIn. In the campaigns that we’ve run on our own platform over the last year, we’ve found that testing subtle variations can drive big increases in engagement and ROI. That’s why I’m really excited about new functionality that we rolled out last week to everyone sponsoring content directly in the LinkedIn feed.
It’s a simple change but one that can make a big difference to how easy it is to run A/B testing on LinkedIn. In a nutshell, you can now test the different elements of your Direct Sponsored Content, maximise engagement and increase your Return on Investment (ROI) with just a few clicks.
We’ve added a new duplication functionality that means you can create a new piece of Direct Sponsored Content by copying the text, link and image of an existing post. You are then free to edit the duplicate post before saving it, changing the element that you want to test, and then running both versions as Direct Sponsored Content, published to the feed of your target audiences.
A/B testing made easy for Direct Sponsored Content
Why does this matter? Well, for starters, it makes it a lot easier and less time-consuming to run A/B tests on the content you sponsor. Doing away with the need to create new posts from scratch means less repetition – and less opportunity for errors to creep in. My hope is that being able to duplicate Direct Sponsored Content campaigns easily will get everybody into the habit of running tests on headlines, calls to action and other elements as a matter of course.
One of the first things that strikes you when you start to A/B test content regularly, is how tricky it is to predict which version of a particular campaign will be most successful. Human attention can be hard to second-guess, even for experienced marketers. Continuous testing will help focus your budget on the best version, and it will also help you to keep learning and refining your approach.
The right approach to A/B testing for content
The second really useful feature of duplicate Direct Sponsored Content is that it sets up your testing in the right way. A/B tests are most valuable when they involve varying just one element in a campaign. That focuses you on producing the best piece of content that you possibly can for your audience and then exploring if one subtle change can make a difference. The alternative approach is to try different versions of everything: copy, headline, image, you name it. Not only does this involve more investment and effort – it also produces far less actionable learnings. Which of the many elements that you changed actually made a difference? You’ll be no closer to finding out.
Subtle variation was very much the approach we took when we made testing part of our mantra at LinkedIn last year. We got ourselves into the habit of A/B testing all of our Direct Sponsored Content campaigns as part of this strategy – and those tests made a huge contribution to quadrupling the effectiveness of our marketing on LinkedIn.
The biggest lesson from our tests? Keep on testing…
We surfaced lots of interesting creative insights on the ideal length of CTAs and the features of images that seem to drive the greatest engagement. However, the biggest insight that we came away with was that, no matter how much you think you know about engaging your audience, it pays to keep testing anyway.
Human attention has always been a moving target. The rules of engagement change as you target different groups of people and also as those people engage on different platforms (as more people engage with LinkedIn content on mobiles, for example). Smart, subtle A/B testing will help you to keep hitting that target – and it’s now easier than ever to carry out those tests on our platform.